Integrating CUDA Streams with Tokio using File Descriptor-Based Polling

Issue Overview

Users are attempting to integrate CUDA streams with the Tokio library, which provides the AsyncFd interface for triggering actions when a file descriptor is readable and/or writable. The goal is to have a file descriptor that becomes readable and/or writable when a CUDA stream completes a given operation. This would allow seamless integration of CUDA streams with Tokio’s event-driven architecture.

The issue specifically pertains to the Nvidia Jetson Orin Nano development board running the Linux for Tegra (L4T) operating system. Users are seeking a way to expose a file descriptor that can be polled to wait for a CUDA stream to reach a certain point in its execution.

Possible Causes

1. Lack of direct CUDA API support: The CUDA library does not provide a direct mechanism to expose a file descriptor that can be polled to wait for a CUDA stream’s completion. The existing APIs, such as CUDA events and cudaIpcGetEventHandle, do not explicitly support this functionality.

2. Platform-specific limitations: The desired functionality may be limited to specific platforms, such as L4T running on the Orin Nano. It may not be available on other operating systems like Windows or when using discrete GPUs.

3. Performance considerations: Manual approaches using cudaLaunchHostFunc could potentially introduce overhead due to additional thread context switches. There may also be limitations related to adding dependencies between work on independent streams.

Troubleshooting Steps, Solutions & Fixes

1. Investigate NvSCI (NVIDIA Software Communication Interface):

   • NvSCI is designed for Inter-Process Communication (IPC) and may provide a solution for integrating CUDA streams with file descriptor-based polling.
   • Refer to the NvSCI documentation for L4T: https://developer.download.nvidia.com/assets/embedded/secure/jetson/docs/NVSCI-L4T.pdf
   • Explore the possibility of preparing an NvSciIpc Endpoint for read/write operations, which could potentially expose a file descriptor for polling.

2. Consider alternative synchronization mechanisms:

   • Evaluate the feasibility of using CUDA events (cudaEvent_t) for synchronization purposes, even if they don’t directly expose a file descriptor.
   • Investigate if CUDA events can be used in combination with other synchronization primitives or platform-specific APIs to achieve the desired behavior.

3. Explore platform-specific APIs:

   • Research if there are any platform-specific APIs or extensions available on L4T that could facilitate the exposure of a file descriptor for CUDA stream synchronization.
   • Look into the possibility of using Linux-specific mechanisms, such as eventfd or pipes, in conjunction with CUDA APIs like cudaImportExternalSemaphore.

4. Engage with the NVIDIA developer community:

   • Reach out to the NVIDIA developer forums or support channels to seek further guidance and insights from experts familiar with L4T and the Orin Nano.
   • Provide detailed information about your use case, requirements, and any attempted solutions to facilitate a more targeted discussion.

5. Consider alternative design approaches:

   • If the desired functionality proves to be infeasible or introduces significant performance overhead, consider alternative design approaches that align with the available CUDA APIs and best practices.
   • Evaluate if the synchronization requirements can be met using different mechanisms, such as callbacks, polling, or event-driven programming paradigms supported by CUDA.

It is worth bringing up that the lack of direct support for exposing a file descriptor to poll CUDA streams may require exploring workarounds or alternative approaches. Further investigation and experimentation may be necessary to find a suitable solution that meets the specific requirements of integrating CUDA streams with Tokio on the Nvidia Jetson Orin Nano development board running L4T.